Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/zuora/zuora-coding-agent/generate-featurenpx skills add zuora/zuora-coding-agent --skill generate-featuregit clone --depth 1 https://github.com/zuora/zuora-coding-agentWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00024 | $0.00729 |
| Opus 5 | $0.00012 | $0.00365 |
| Sonnet 5 | $0.00005 | $0.00146 |
| Haiku 4.5 | $0.00002 | $0.00073 |
Grade A, and why
zuora-uat-generate-feature scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate feature worker (internal)
Inputs: feature, optional tr_filter (TR numbers), force_overwrite, verify, environment, max_fix_retries.
Flow (per TR in scope)
- Plan —
${CLAUDE_PLUGIN_ROOT}/skills/zuora-uat/plan/SKILL.md - API script —
generate-api/SKILL.md(gap-fill) - UI doc —
generate-ui/SKILL.mdwhen hybrid (gap-fill) - UI placement check (hybrid TRs only) — verify doc is in execution, not testplan (see below)
- On artifact rewrite: clear verification mark for that TR:
python3 "${CLAUDE_PLUGIN_ROOT}/references/uat-test/execution/scripts/uat_verification.py" clear \
--scenario-dir "$UAT_ROOT/execution/tests/test_scenarios/<folder>" --tr <n>
- Verify segment when
verify=true—verify/SKILL.mdwithenvironment - When
verify=false: setverified: falsefor affected TRs (sameclearcommand as step 5, per TR in scope) - Required — finalize verification marks before returning JSON:
python3 "${CLAUDE_PLUGIN_ROOT}/references/uat-test/execution/scripts/uat_verification.py" finalize-generate \
--git-root "$GIT_ROOT" \
--feature "<feature>" \
--verify "<verify>"
# append --tr N when tr_filter is set
UI placement check (after step 3, hybrid TRs)
Fail fast if ui_steps_tr{n}.md is missing from execution or present under testplan:
# A. Execution doc must exist
PYTHONPATH="$UAT_ROOT/execution/tests" python3 -c \
"from test_utils.repo_paths import resolve_ui_steps_doc_path; resolve_ui_steps_doc_path('<feature>', '<TRn>')"
# B. No stray UI docs in testplan for this feature
test -z "$(find "$UAT_ROOT/design/testplan" -path '*<feature>*' -name 'ui_steps_tr*.md' -print)"
On failure: move misplaced file from testplan to the resolved execution path (or delete and rewrite), then retry the check once. If still failing, return worker JSON with a failures entry for that TR.
TR list
tr_filternull → all TRs from plan folder- else → only listed TR numbers
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 76 lines · 24 tokens per session scan A 83cd720ed144
zuora-uat-generate-feature is a skill published in the GitHub repository zuora/zuora-coding-agent (2 stars, last pushed 16d ago), licensed MIT. It adds 24 tokens to every session and 729 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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